{"id":"W1023933770","doi":"10.1139/cjfr-2017-0220","title":"An impact analysis of climate change on the forestry industry in Quebec","year":2017,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Climate Change Policy and Economics","field":"Economics, Econometrics and Finance","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Stedfast (Canada); Université de Sherbrooke","funders":"Natural Resources Canada","keywords":"Climate change; Computable general equilibrium; Forest product; Population; Gross domestic product; Goods and services; Natural resource economics; Product (mathematics); Geography; Forestry; Economics; Agricultural economics; Ecology; Forest management; Economy; Economic growth","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003367003,0.0001098647,0.0004686702,0.0023381,0.000376177,0.0003292888,0.001075598,0.0002872244,0.0006314924],"category_scores_gemma":[0.0006184175,0.00009238347,0.0002306309,0.0004587739,0.000311474,0.0005075562,0.00004089852,0.001174197,0.00003665458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005385141,"about_ca_system_score_gemma":0.0003149447,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5707512,"about_ca_topic_score_gemma":0.9380351,"domain_scores_codex":[0.9984403,0.00005237559,0.0006105833,0.000170662,0.00006601852,0.0006600465],"domain_scores_gemma":[0.99788,0.0001569101,0.0006119082,0.0007535653,0.000103621,0.0004939745],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002885201,0.0000313547,0.9483171,0.000009038725,0.0001186552,0.00003645185,0.001013388,0.0003396521,6.089604e-7,0.04924963,0.0001786725,0.0006765843],"study_design_scores_gemma":[0.000257323,0.0001755041,0.9905074,0.00005052207,0.00001220779,0.000003433467,0.0004468064,0.001458231,0.000007290328,0.006277182,0.0007145554,0.00008956723],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9879281,0.0002476668,0.000001067595,0.003281339,0.0001136989,0.00012206,0.0005575266,8.532026e-7,0.007747679],"genre_scores_gemma":[0.9992381,0.0003161128,0.000006625892,0.0001089315,0.0002351118,0.000008214889,0.000008149193,0.00001560773,0.00006310696],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3672839,"threshold_uncertainty_score":0.6914399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3738831224854106,"score_gpt":0.4081328225642494,"score_spread":0.03424970007883882,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}